With recent advances in molecular biology, it is now possible to identify genetic events that lead to malignancy. In particular, chromosomal translocations that result in the expression of novel leukemogenic fusion proteins have been identified, and the genes encoding these proteins have been cloned from patients with leukemia. Ultimately, these gene rearrangements may serve as targets for novel therapies. Additionally, fusion genes arising, from somatic mutations may be used a markers of malignancy that allow clinical investigators to monitor patients' response to therapy. Thus, these gene rearrangements might therefore be used to identify and follow groups of patients who could benefit from a specific treatment. This project will create a paradigm for exploring the integration of molecular genetics into clinical investigation using the two most commonly occurring gene rearrangements in childhood acute lymphoblastic leukemia. The first specific aim of this proposal is to prospectively determine the prognostic significance of TEL/AML1 in patients treated on DFCI-ALL Consortium protocols. TEL/AML1 is the most common fusion gene known to occur in any pediatric malignancy. Though initially reported to confer a favorable prognosis, recent analyses from Europe indicate that the TEL/AML1 fusion occurs with the same frequency at relapse as it dose at initial diagnosis. There is thus controversy over the prognostic significance of the TEL/AML1 gene rearrangement. The second specific aim of this proposal is to use quantitative RT-PCR techniques on serial samples to determine the prognostic significance of TEL/AML1 transcript copy number. The third specific aim is to apply quantitative RT-PCR techniques to pediatric leukemias associated with the E2A/PBX1 gene rearrangement. The second and third specific aims are based on the premise developed in analysis of other leukemias that fusion transcript copy number is a predictor of clinical outcome. Advances in molecular technology are heralding an era when genetic testing will become routine for many diseases. It is an ideal time to develop simple and efficient quantitative approaches to minimal residual disease detection; we can capitalize on the growing number of discoveries in molecular genetics and thereby maximize the treatment of childhood acute lymphoblastic leukemia.